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What (who) is S-factor - definition

S-factor

In nuclear physics, the astrophysical S-factor is a rescaling of a nuclear reaction's total cross section to account for the Coulomb repulsion between the charged reactants. It determines the rates of nuclear fusion reactions that occur in the cores of stars.

https://en.wikipedia.org/wiki/S-factor

Factor analysis

$^2=h^2_a</math>. If another data vector <math>\mathbf{z}_b</math> were plotted, the cosine of the angle between <math>\mathbf{z}_a</math> and <math>\mathbf{z}_b</math> would be <math>r_{ab}</math> : the <math>(a,b)</math>-entry in the correlation matrix. (Adapted from Harman Fig. 4.3)<ref name="Harman"/>$

STATISTICAL METHOD USED TO DESCRIBE CORRELATION THROUGH FEWER POSSIBLY LATENT VARIABLES

Factor analysis (in marketing); Factor Analysis; Multi-factorial; Factor loadings; Factorial analysis; Higher-order factor analysis; Principal factor analysis; Factor loading; Factor weight; Factor analyses; Statistical factor analysis

Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables.

https://en.wikipedia.org/wiki/Factor_analysis

factor analysis

$^2=h^2_a</math>. If another data vector <math>\mathbf{z}_b</math> were plotted, the cosine of the angle between <math>\mathbf{z}_a</math> and <math>\mathbf{z}_b</math> would be <math>r_{ab}</math> : the <math>(a,b)</math>-entry in the correlation matrix. (Adapted from Harman Fig. 4.3)<ref name="Harman"/>$

STATISTICAL METHOD USED TO DESCRIBE CORRELATION THROUGH FEWER POSSIBLY LATENT VARIABLES

Factor analysis (in marketing); Factor Analysis; Multi-factorial; Factor loadings; Factorial analysis; Higher-order factor analysis; Principal factor analysis; Factor loading; Factor weight; Factor analyses; Statistical factor analysis

¦ noun Statistics a process in which the values of observed data are expressed as functions of a number of possible causes to determine which are most important.